180 citations
- Massachusetts Institute of TechnologyUS38 papers
- University of BonnDE37 papers
- University of OxfordGB36 papers
- Centre National de la Recherche ScientifiqueFR35 papers
- Centro Brasileiro de Pesquisas FísicasBR35 papers
- École Polytechnique Fédérale de LausanneCH35 papers
- Lamarr Institute for Machine Learning and Artificial Intelligence35 papers
- Ruhr University BochumDE35 papers
- Sorbonne UniversitéFR35 papers
- University of BolognaIT35 papers
- University of CambridgeGB35 papers
- University of SienaIT35 papers
6 papers · 1 filter
Fréchet Wavelet Distance: A Domain-Agnostic Metric for Image Generation
Lokesh Veeramacheneni, Moritz Wolter, Hildegard Kuehne +1
Modern metrics for generative learning like Fréchet Inception Distance (FID) and DINOv2-Fréchet Distance (FD-DINOv2) demonstrate impressive performance. However, they suffer from v…
Simple and Effective Input Reformulations for Translation
Brian Yu, Hansen Lillemark, Kurt Keutzer
Foundation language models learn from their finetuning input context in different ways. In this paper, we reformulate inputs during finetuning for challenging translation tasks, le…
A Theory of Bounded Inductive Rationality
Caspar Oesterheld, Abram Demski, Vincent Conitzer
The dominant theories of rational choice assume logical omniscience. That is, they assume that when facing a decision problem, an agent can perform all relevant computations and de…
Semantically-Prompted Language Models Improve Visual Descriptions
Michael Ogezi, Bradley Hauer, Grzegorz Kondrak
Language-vision models like CLIP have made significant strides in vision tasks, such as zero-shot image classification (ZSIC). However, generating specific and expressive visual de…
PhenoBench -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain
Jan Weyler, Federico Magistri, Elias Marks +6
The production of food, feed, fiber, and fuel is a key task of agriculture, which has to cope with many challenges in the upcoming decades, e.g., a higher demand, climate change, l…
Towards a Scalable Proof Engine: A Performant Prototype Rewriting Primitive for Coq
Jason Gross, Andres Erbsen, Jade Philipoom +2
We address the challenges of scaling verification efforts to match the increasing complexity and size of systems. We propose a research agenda aimed at building a performant proof…